Activated Protein C Improves Ischemic Flap Survival and Modulates Proangiogenic and Antiinflammatory Gene Expression
Bibliographic record
Abstract
BACKGROUND: Flap necrosis remains a major complication in reconstructive surgery. The authors evaluated whether systemic activated protein C, a natural serum anticoagulant with anti-inflammatory, proangiogenic, and cytoprotective properties, can improve ischemic skin flap survival. METHODS: Cranially based dorsal cutaneous flaps were elevated on 44 rats. Animals received intravenous injections of activated protein C (25 microg/kg) or saline. Rats were divided into three groups depending on the timing of the first injection: postoperative (45 minutes postoperatively, n = 12), late preoperative (45 minutes preoperatively, n = 5), and early preoperative (3 hours preoperatively, n = 5). In all groups, second and third injections were performed at 3 and 24 hours postoperatively. Flap survival was measured on day 7. Histological and real-time polymerase chain reaction specimens were collected on days 2 and 7 and at 3 and 24 hours, respectively. RESULTS: Postoperative activated protein C improved flap survival (68.9 +/- 4.3 percent) compared with control treatment (39.3 +/- 1.5 percent; p < 0.001). Late preoperative treatment produced diffuse flap hemorrhage. Early preoperative activated protein C injection produced near-complete flap survival (96.1 +/- 1.1 percent for activated protein C versus 50.1 +/- 3.3 percent for control; p < 0.001). Significantly fewer inflammatory cells, improved muscle viability, and increased blood vessel density were observed in activated protein C-treated versus control rats. Activated protein C treatment significantly reduced mRNA levels of intercellular adhesion molecule-1 and tumor necrosis factor-alpha, while increasing levels of Egr-1, vascular endothelial growth factor receptor 2, and Bcl-2. CONCLUSIONS: Systemic activated protein C modulates genes involved in angiogenesis, inflammation and apoptosis and improves ischemic flap survival.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".